Sensorless Condition Monitoring of Feed Axis Components in Production Systems by Applying Prony Analysis

Chris Schöberlein, Johannes Quellmalz, Holger Schlegel, Martin Dix

2022

Abstract

Condition monitoring of modern production systems has established itself as an independent area of research in recent years. Main goal is to achieve an increase in machine productivity by reducing downtime and maintenance costs. In particular, the installed electromechanical axes offer great potential for improvement. Besides an installation of additional sensors, modern drive systems also provide various signals suitable for superordinated monitoring systems. The paper presents a novel approach for monitoring of specific mechanical axis components based solely on internal control loop signals. Fundamental idea is to combine a parametric approach for vibration analysis, the so-called Prony analysis, with a drive-based setpoint generation and data aquisition. The method is verified by detecting emulated malfunctions on a single-axis test stand and a three-axis vertical milling machining center. Experimental investigations prove that the presented approach is capable of reliably detecting the artificially introduced defects on different axis components.

Paper Citation

in Harvard Style

Schöberlein C., Quellmalz J., Schlegel H. and Dix M. (2022). Sensorless Condition Monitoring of Feed Axis Components in Production Systems by Applying Prony Analysis. In Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-585-2, pages 214-221. DOI: 10.5220/0011287200003271

in Bibtex Style

@conference{icinco22,
author={Chris Schöberlein and Johannes Quellmalz and Holger Schlegel and Martin Dix},
title={Sensorless Condition Monitoring of Feed Axis Components in Production Systems by Applying Prony Analysis},
booktitle={Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2022},
pages={214-221},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011287200003271},
isbn={978-989-758-585-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 19th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Sensorless Condition Monitoring of Feed Axis Components in Production Systems by Applying Prony Analysis
SN - 978-989-758-585-2
AU - Schöberlein C.
AU - Quellmalz J.
AU - Schlegel H.
AU - Dix M.
PY - 2022
SP - 214
EP - 221
DO - 10.5220/0011287200003271